Struct easy_ml::tensors::views::TensorRename

pub struct TensorRename<T, S, const D: usize> { /* private fields */ }

A combination of new dimension names and a tensor.

The provided dimension names override the dimension names in the view_shape of the TensorRef exposed.

use easy_ml::tensors::Tensor;
use easy_ml::tensors::views::{TensorRename, TensorView};
let a_b = Tensor::from([("a", 2), ("b", 2)], (0..4).collect());
let b_c = TensorView::from(TensorRename::from(&a_b, ["b", "c"]));
let also_b_c = a_b.rename_view(["b", "c"]);
assert_ne!(a_b, b_c);
assert_eq!(b_c, also_b_c);

Implementations

impl<T, S, const D: usize> TensorRename<T, S, D>where
    S: TensorRef<T, D>,

pub fn from(source: S, dimensions: [Dimension; D]) -> TensorRename<T, S, D>

Creates a TensorRename from a source and a list of dimension names to override the view_shape with.

Panics

• If a dimension name is not unique

pub fn source(self) -> S

Consumes the TensorRename, yielding the source it was created from.

pub fn source_ref(&self) -> &S

Gives a reference to the TensorRename’s source (in which the dimension names may be different).

pub fn source_ref_mut(&mut self) -> &mut S

Gives a mutable reference to the TensorRename’s source (in which the dimension names may be different).

pub fn get_names(&self) -> &[Dimension; D]

Gets the dimension names this TensorRename is overriding the source it was created from with.

pub fn set_names(&mut self, dimensions: [Dimension; D])

Sets the dimension names this TensorRename is overriding the source it was created from with.

Panics

• If a dimension name is not unique

Trait Implementations

impl<T: Clone, S: Clone, const D: usize> Clone for TensorRename<T, S, D>

fn clone(&self) -> TensorRename<T, S, D>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<T: Debug, S: Debug, const D: usize> Debug for TensorRename<T, S, D>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<T, S, const D: usize> TensorMut<T, D> for TensorRename<T, S, D>where
    S: TensorMut<T, D>,

A TensorRename implements TensorMut, with the dimension names the TensorRename was created with overriding the dimension names in the original source.

fn get_reference_mut(&mut self, indexes: [usize; D]) -> Option<&mut T>

Gets a mutable reference to the value at the index, if the index is in range. Otherwise returns None.

unsafe fn get_reference_unchecked_mut(&mut self, indexes: [usize; D]) -> &mut T

Gets a mutable reference to the value at the index without doing any bounds checking. For a safe alternative see get_reference_mut.

impl<T, S, const D: usize> TensorRef<T, D> for TensorRename<T, S, D>where
    S: TensorRef<T, D>,

A TensorRename implements TensorRef, with the dimension names the TensorRename was created with overriding the dimension names in the original source.

fn get_reference(&self, indexes: [usize; D]) -> Option<&T>

Gets a reference to the value at the index if the index is in range. Otherwise returns None.

fn view_shape(&self) -> [(Dimension, usize); D]

The shape this tensor has. See dimensions for an overview. The product of the lengths in the pairs define how many elements are in the tensor (or the portion of it that is visible).

unsafe fn get_reference_unchecked(&self, indexes: [usize; D]) -> &T

Gets a reference to the value at the index without doing any bounds checking. For a safe alternative see get_reference.

fn data_layout(&self) -> DataLayout<D>

The way the data in this tensor is laid out in memory. In particular, Linear has several requirements on what is returned that must be upheld by implementations of this trait.